基于加权实数编码遗传算法的超材料优化设计

摘要

针对超材料优化设计参数多、权重各异的特点，提出一种基于加权实数编码的遗传算法。该算法采用等位基因或双倍基因实现对遗传基因的加权编码，是二进制编码中加权思想的推广。与普通遗传算法相比，加权实数编码遗传算法加入了人工选择因素，既可以加快种群收敛速度，又可以提高算法的求解质量，尤其适用于种群规模较大的遗传优化计算。文中以一个超材料吸波体的优化设计为例，对算法进行了验证。%A weighted real-coded genetic algorithm is proposed in this paper, in allusion to the characteristics of optimizing designs of metamaterials, which have many parameters and parameters of different powers in metamaterial structure. The algorithm utilizing allele or double gene to change the power of one gene, develops the idea of weighted encoded binary coding. Compared with common real-coded based genetic algorithm, the weighted real-coded genetic algorithm adds artificial selection in it, it can not only accelerate the speed of convergence, but also improve the solution quality, especially for the design of large-scale and long computation time. In this paper, the algorithm is verified by optimizing a metamaterial absorber.